Features robust to misregistration of a target object and illumination variation can be extracted by calculating a plurality of co-occurrence histograms of oriented gradients from image data (see Tomoki Watanabe, Satoshi Ito, and Kentaro Yokoi, “Co-occurrence Histograms of Oriented Gradients for Pedestrian Detection,” The 3rd Pacific-Rim Symposium on Image and Video Technology, LNCS 5414, pages 37-47, 2009). According to this technology, features that are effective for detecting a target object such as a pedestrian can be extracted, for example.
According to “Co-occurrence Histograms of Oriented Gradients for Pedestrian Detection,” however, since pixels in the image data are handled uniformly, the discrimination power of features is not sufficient when a plurality of target objects are included or when a foreground and a background are present in an image represented by the image data.